Comparison
local-deep-research vs storm
Verdict
Pick local-deep-research if for deep research locally encrypted, supports retrieval-augmented generation using diverse LLM frameworks on local GPU or cloud, searches through arXiv, PubMed, personal documents; pick storm if storm is an advanced AI tool that utilizes LLM technology and RAG to generate deep research reports with citations.
Markdown twin · local-deep-research alternatives · storm alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | local-deep-research | storm |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1w · github_public_v1 | Slowing (320d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Organization account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- local-deep-research
- Supports local and cloud LLMs with encrypted search from diverse sources.
- storm
- An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Stars
- local-deep-research
- 8.9k
- storm
- 31k
Forks
- local-deep-research
- 788
- storm
- 2.9k
Open issues
- local-deep-research
- 352
- storm
- 108
Language
- local-deep-research
- Python
- storm
- Python
Adopt for
- local-deep-research
- For deep research locally encrypted, supports retrieval-augmented generation using diverse LLM frameworks on local GPU or cloud, searches through arXiv, PubMed, personal documents.
- storm
- Storm is an advanced AI tool that utilizes LLM technology and RAG to generate deep research reports with citations.
Persona
- local-deep-research
- -
- storm
- -
Runtime
- local-deep-research
- -
- storm
- -
License
- local-deep-research
- MIT
- storm
- MIT
Last pushed
- local-deep-research
- Aug 12, 2026
- storm
- Sep 30, 2025
Categories
- local-deep-research
- Data & Retrieval, LLM Frameworks
- storm
- Data & Retrieval, LLM Frameworks
Trust and health
Maintenance
- local-deep-research
- Very active (96%)
- storm
- Slowing (36%)
Days since push
- local-deep-research
- 0d
- storm
- 320d
Open issues (now)
- local-deep-research
- 352
- storm
- 108
Stars delta
- local-deep-research
- Unknown
- storm
- +895 (30d)
Open issues delta
- local-deep-research
- Unknown
- storm
- -36 (30d)
Owner type
- local-deep-research
- User
- storm
- Organization
Full report
- local-deep-research
- Trust report
- storm
- Trust report
Choose local-deep-research if…
- Tags unique to local-deep-research: academia, anthropic, arxiv, encryption.
- local-deep-research ships Docker support for self-hosted deployment.
- You need encryption for all data processing steps and want support for various sources like academic articles and personal files.
When NOT to use local-deep-research
- If you require real-time collaboration features that are not supported by this tool's framework.
- In scenarios where online connectivity is unreliable and external search engine support is considered critical.
Choose storm if…
- Tags unique to storm: agentic-rag, deep-research, knowledge-curation, large language models.
- When you need comprehensive reports that are heavily researched and reference a wide variety of sources.
- More GitHub stars (31k vs 8.9k) - visibility, not fit.
When NOT to use storm
- When real-time interaction or rapid iterative feedback loops are necessary, as Storm’s focus on thorough research might lead to longer processing times.
- In scenarios requiring manual curation and subjective analysis that goes beyond the capabilities of retrieval and generation mechanisms.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (LearningCircuit/local-deep-research) · observed Aug 12, 2026
- GitHub forks (LearningCircuit/local-deep-research) · observed Aug 12, 2026
- Last push (LearningCircuit/local-deep-research) · observed Aug 12, 2026
- License file (MIT) · observed Aug 12, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (stanford-oval/storm) · observed Aug 17, 2026
- GitHub forks (stanford-oval/storm) · observed Aug 17, 2026
- Last push (stanford-oval/storm) · observed Sep 30, 2025
- License file (MIT) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: local-deep-research 8.9k · storm 31k (synced Aug 12, 2026).
Common questions
- What is the difference between local-deep-research and storm?
- local-deep-research: Supports local and cloud LLMs with encrypted search from diverse sources.. storm: An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.. See the comparison table for live GitHub stats and shared categories.
- When should I choose local-deep-research over storm?
- Choose local-deep-research over storm when Tags unique to local-deep-research: academia, anthropic, arxiv, encryption; local-deep-research ships Docker support for self-hosted deployment; You need encryption for all data processing steps and want support for various sources like academic articles and personal files.
- When should I choose storm over local-deep-research?
- Choose storm over local-deep-research when Tags unique to storm: agentic-rag, deep-research, knowledge-curation, large language models; When you need comprehensive reports that are heavily researched and reference a wide variety of sources; More GitHub stars (31k vs 8.9k) - visibility, not fit.
- When should I avoid local-deep-research?
- If you require real-time collaboration features that are not supported by this tool's framework. In scenarios where online connectivity is unreliable and external search engine support is considered critical.
- When should I avoid storm?
- When real-time interaction or rapid iterative feedback loops are necessary, as Storm’s focus on thorough research might lead to longer processing times. In scenarios requiring manual curation and subjective analysis that goes beyond the capabilities of retrieval and generation mechanisms.
- Is local-deep-research or storm more popular on GitHub?
- storm has more GitHub stars (31,026 vs 8,900). Stars measure visibility, not whether either tool fits your constraints.
- Are local-deep-research and storm open source?
- Yes - both are open-source projects on GitHub (local-deep-research: MIT, storm: MIT).
- Where can I find alternatives to local-deep-research or storm?
- GraphCanon lists graph-backed alternatives at local-deep-research alternatives and storm alternatives (local-deep-research markdown twin, storm markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, local-deep-research or storm?
- local-deep-research: Very active. storm: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for local-deep-research and storm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: local-deep-research trust report; storm trust report.